Who Fills the Gaps in Lending When Monetary Policy Tightens? (2007-2023)

Introduction

Monetary tightening is often thought to be shifting lending activity away from banks and toward alternative financial intermediaries. Policy rates rising and/or credit standards tightening may decrease bank lending, potentially allowing for changes in credit composition via non-bank lenders. Post-Covid, the Bank of England (BoE) raised the Bank Rate from near the Zero Lower Bound (ZLB) to 5.25 percent, its highest level since before the Global Financial Crisis (GFC).1 This tightening cycle provides a setting to examine credit composition response mechanisms to policy shocks.

 

This article aims to find evidence and discuss whether short-run lending tightening shocks have significant effects on share of lending provided by non-bank institutions in the UK using quarterly data from 2007 to 2023. Credit composition appears highly persistent and evolves gradually rather than responsive to short-term changes. Results suggest that long-run structural forces, especially post-GFC regulatory reforms, play a more important role than short-run monetary tightening in shaping the UK credit landscape.

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Economic Framework

In building the analysis regarding credit composition structures, I utilise two main economic frameworks as a basis. I will be mentioning the credit channel of monetary policy transmission by Bernanke and Gertler in 1995 with the bank capital channel work of Van den Heuvel in 2002. The second framework is the structural differences in financial systems by Allen and Gale in 2000.

 

Bernanke and Gertler formalise how credit frictions amplify monetary transmission through bank-dependent borrowers.2 Policy tightening raises funding costs and constraints regarding capital can become more binding, reducing banks’ ability to expand balance sheets, requiring other intermediaries to step in. Further, Van den Heuvel shows that tighter monetary conditions can limit lending, specifically in capital-intensive banking systems like the UK, when capital requirements bind.3 This means monetary tightening may reduce bank credit growth, creating space for others.

 

Allen and Gale on the other hand, argue that institutional structure shapes credit flows.4 After the GFC, non-bank intermediation expanded especially through securitised and shadow banking channels.5 With Basel III capital and liquidity reforms changing bank lending capacity, I use this framework as institutional changes post-GFC affecting credit flows, creating a financial system with more availability for non-bank lending in the UK. This framework also proposes a possibility of credit composition changes reflecting more long-term structural changes than short-run responses to tightening shocks.

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Data and Methodology

The analysis uses quarterly UK data from 2007 Q2 until 2023 Q2. The dependent variable, NonBankShare, measures the proportion of total corporate lending provided by non-bank financial intermediaries relative to total lending. I construct this variable using Office for National Statistics (ONS) Flow of Funds data.6 Monetary tightening, variable NetTightening, is measured using BoE’s Credit Conditions Survey net percentage balance for the availability of credit to corporates.7 To account for structural shifts in the monetary and regulatory environment, a post-2016 regime dummy is included accounting for the ZLB and post-ZLB eras. Given a strong persistence in credit composition, the main specification employs a dynamic model with a lagged dependent variable and heteroskedasticity and autocorrelation-consistent (HAC) standard errors.

 

All variables are seasonally adjusted where applicable and ordered chronologically. The inclusion of the lagged dependent variable captures path dependence in credit shares, while HAC standard errors ensure robust statistical inference.

 

Though the Bank Rate8, real GDP growth9, and bond yield data10 were included in the initial specification, they are not included in the final model due to lack of explanation of the dependent variable. Unused specifications can be found in the appendix.

 

NonBankSharet=+NonBankSharet-1+1NetTighteningt+2Post2016t+3(NetTighteningtPost2016t+t

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Results and Discussion

The dynamic HAC regression indicates that NonBankShare is highly persistent, with the lagged dependent variable statistically significant and explaining the majority of the variation. This suggests that credit composition has gradual adjustment and has strong path dependence.

 

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Figure 1 - Autocorrelation function plot for NonBankShare

 

Once persistence is accounted for as necessary, seen in Figure 1, neither NetTightening or its interaction with the regime dummy is statistically significant. These findings imply that quarterly tightening shocks do not create shifts toward non-bank intermediation in credit composition mechanically, illustrated in Table 1.

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Table 1 - Dynamic HAC Regression

 

Earlier level regressions without dynamics did suggest some apparent relationships, however, they were driven by serial correlation, as seen by low Durbin-Watson statistics. The short-run tightening narrative weakens substantially when autocorrelation is corrected along with incorporated persistence.

 

The evidence supports a more structural interpretation, like the suggested relationship in the financial systems framework. Post-crisis regulatory reforms, particularly Basel III standards, may have changed bank balance sheet behavior over time due to lower availability of high leverage, high lending behavior.11 Shadow banking and market-based finance showed expansion in a broader transformation in financial intermediation as argued by Adrian and Ashcraft.12 These are gradual developments that evolved over years rather than short-term responses to tightening quarters.

 

Then how has private credit boomed since 2021 and why do many private markets-based financial firms see such an opportunity in non-bank lending to corporates? The AUM of private credit assets is expected to double by the year 2030 from about $2.28 trillion in 2025.13 This analysis allows us to see that this growing market has been shaping for years with changing conditions in market-based financial systems.

 

The absence of short-run substitution does not contradict the rise of private credit when the data and economic frameworks are connected. Rather, it indicates that the cumulation of regulatory, and institutional changes gradually shifted incentives toward more market-based intermediation in lending.

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Conclusion

This article examines whether monetary tightening shifts lending toward non-bank financial intermediaries in the UK. Using quarterly data from 2007 to 2023 and dynamic regression methods, it does not find significant evidence that short-run tightening shocks have major effects on credit composition. Rather, NonBankShare shows strong persistence, suggesting stronger structural forces than short-run cyclical movements.

 

Findings point toward long-run institutional change, regulatory reform, and financial innovation in alternative investments as primary drivers of credit composition changes. Credit structure seems to adjust gradually as financial institutions adapt to evolving environments rather than responding directly to tightening episodes. 

 

Speculation can be made regarding why structural changes over the past decade affecting credit composition have come to fruition only in the past few years. However, without primary-data driven research with direct balance sheet analysis, such speculations will be filled with confounding variables and lacking explanation of macroeconomic phenomena.

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References

1. Bank of England, Bank Rate history and data, accessed February 10, 2026, https://www.bankofengland.co.uk/boeapps/database/Bank-Rate.asp.

2. Ben S. Bernanke and Mark Gertler, “Inside the Black Box: The Credit Channel of Monetary Policy Transmission,” Journal of Economic Perspectives 9, no. 4 (Fall 1995): 27–48, accessed February 12, 2026, https://www.aeaweb.org/articles?id=10.1257/jep.9.4.27.

3. Skander J. Van den Heuvel, “The Bank Capital Channel of Monetary Policy” (paper, Society for Economic Dynamics Meeting Papers 512, 2006), accessed February 12, 2026, https://www.researchgate.net/publication/24122358_The_Bank_Capital_Channel_of_Monetary_Policy.

4. Franklin Allen and Douglas Gale, Comparing Financial Systems (Cambridge, MA: The MIT Press, 2000), accessed February 12, 2026, https://www.scribd.com/document/900171996/Comparing-Financial-Systems-by-Franklin-Allen-Douglas-Gale-z-Lib-org.

5. Gary B. Gorton and Andrew Metrick, “Securitized Banking and the Run on Repo,” NBER Working Paper No. 15223 (Cambridge, MA: National Bureau of Economic Research, August 2009), accessed February 16, 2026, https://www.nber.org/system/files/working_papers/w15223/w15223.pdf.

6. Office for National Statistics (ONS), UK Economic Accounts: flow of funds dataset, “Current” edition, accessed February 14, 2026, https://www.ons.gov.uk/economy/nationalaccounts/uksectoraccounts/datasets/unitedkingdomeconomicaccountsflowoffunds/current.

7. Bank of England, Credit Conditions Survey: 2025 Q4, accessed February 14, 2026, https://www.bankofengland.co.uk/credit-conditions-survey/2025/2025-q4.

8. Bank of England, Bank Rate history and data.

9. Office for National Statistics (ONS), Gross Domestic Product: Quarter on Quarter growth (IHYQ), accessed February 14, 2026, https://www.ons.gov.uk/economy/grossdomesticproductgdp/timeseries/ihyq/qna.

10. Organization for Economic Co-operation and Development, Interest Rates: Long-Term Government Bond Yields: 10-Year: Main (Including Benchmark) for United Kingdom [IRLTLT01GBM156N], FRED: Federal Reserve Bank of St. Louis, accessed February 14, 2026, https://fred.stlouisfed.org/series/IRLTLT01GBM156N.

11. Basel Committee on Banking Supervision, Basel III: A Global Regulatory Framework for More Resilient Banks and Banking Systems, revised June 2011 (Basel, Switzerland: Bank for International Settlements, 2010), accessed February 15, 2026, https://www.bis.org/publ/bcbs189.pdf.

12. Tobias Adrian and Adam B. Ashcraft, “Shadow Banking Regulation,” Federal Reserve Bank of New York Staff Reports no. 559 (April 2012), accessed February 15, 2026, https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr559.pdf.

13. Joyce Guevarra and Neel Hiteshbhai Bharucha, “Private credit gains ground among top private equity managers,” S&P Global Market Intelligence, November 13, 2025, accessed February 15, 2026, https://www.spglobal.com/market-intelligence/en/news-insights/articles/2025/11/private-credit-gains-ground-among-top-private-equity-managers-94290783.

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Appendix

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